1. Field of the Invention
The present invention relates to a learning apparatus and method, a recognition apparatus and method, a program, and a recording medium. More particularly, the present invention relates to a learning apparatus and method, a recognition apparatus and method, a program, and a recording medium whereby target objects can be more reliably detected from an image.
2. Description of the Related Art
In the related art, technology for detecting humans from images has been researched and developed, primarily for security or in-vehicle applications. (See for example: Navneet Dalal and Bill Triggs, “Histograms of Oriented Gradients for Human Detection”, CVPR2005; and B. Wu and R. Nevatia, “Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors”, In Proc. 10th Int. Conf. Computer Vision, 2005.) In such literature, contour feature values obtained by edge detection are used as the primary feature values for detecting (i.e., recognizing) humans from images. With such technologies, many variations of contour feature values obtained by edge detection are defined as new feature values, and human recognition is conducted therewith.
For example, in the technology proposed by Dalal and Triggs feature values are obtained by taking histograms oriented within small regions of edges. By using such feature values, the technology has the advantage of being more resilient to some degree of contour distortion and similar factors.